I met with Barry Morris, the CEO and Founder of NimbusDB at a reception the night before. I had long conversation with him around the issues with legacy databases, NoSQL, and of course NimbusDB. I must say that, after long time, I have seen a company applying all the right design principles to solve a chronic problem - how can you make SQL databases scale so that they don't suck.

One of the main issues with the legacy relational databases is that they were never designed to scale out to begin with. A range of NoSQL solutions addressed the scale-out issue, but the biggest problem with a NoSQL is that NoSQL is not SQL. This is why I was excited when I saw what NimbusDB has to offer: it's a SQL database at the surface but has radically modern architecture underneath that leverages MapReduce to divide and conquer queries, BitTorrent for messaging, and Dynamo for persistence.

NimbusDB's architecture isolates transactions from storage and uses asynchronous messaging across nodes - a non-blocking atom commit protocol - to gain horizontal scalability. At the application layer, it supports the "most" of SQL 99 features and doesn't require the developers to re-learn or re-code. The architecture doesn't involve any kind of sharding and the nodes can scale on any commodity machine on a variety of operating systems. This eliminates an explicit need of a separate hot back-up since any and all nodes serve as a live database in any zone. This makes NimbusDB an always live system, which also solves a major problem with traditional relational databases - high availability. It's an insert only database and it versions every single atom/record. That's how it achieves MVCC as well. The data is compressed on a disk and is accessed from an in-memory node.

I asked Barry about using NimbusDB as an analytic database and he said that the database is currently not optimized for analytic queries, but he does not see why it can't be tuned and configured as an analytic database since the inherent architecture doesn't really have to change. Though, during his pitch, he did mention that NimbusDB may have challenges with heavy reads and heavy writes. I personally believe that solving a problem of analytic query on large volume of data is a much bigger challenge in the cloud due to the inherent distributed nature of the cloud. Similarly, building a heavy-insert system is equally difficult. However, most systems fit somewhere in between. This could be a great target market for NimbusDB.

I haven't played around with the database, but I do intend to do so. On a cursory look, it seems to defy the CAP theorem. Barry seems to disagree with me. The founders of NimbusDB have great backgrounds. Barry was the CEO of IONA and Streambase and has extensive experience in building and leading technology companies. If NimbusDB can execute based on the principles it is designed on, this will be a huge breakthrough.

As a general trend, I see a clear transition, where people finally agree that SQL is still a preferred interface, but the key is to rethink the underlying architecture.

Update: After I published the post, Benjamin Block raised concerns around NimbusDB not getting the CAP theorem. As I mentioned in the post, I also had the same concern, but I would give them benefit of doubt for now and watch the feedback as the product goes into beta.

About me

Chirag MehtaVice President, Product Management and Business Development at SAP.

Email: tochirag at gmail dot com

• A Silicon Valley software executive with entrepreneurial, outside-in, and “General Manager” mindset with 15+ years of experience in product strategy, product design, product architecture, product management, and product development in building and shipping multiple releases of world-class enterprise software—applications, platform, middleware and infrastructure components—for the #1 and #2 enterprise software companies in the world.

• A keynote speaker and a panelist at several enterprise software conferences

• Adjunct faculty with the department of Computer Engineering at Santa Clara University teaching graduate classes

In my current role at SAP, I'm responsible for:

a) Product management activities to explore, identify, and realize Big Data breakthrough scenarios—things that were not feasible before or things customers could not even have imagined they could do—for SAP's most strategic customers, globally, across all industries.

b) Business Development activities to generate net new opportunities as well as developing existing opportunities that contribute to a very large percentage of overall revenue of SAP HANA, the fastest growing product in SAP's history.

c) Working closely with SAP's leadership as well as the executive management team to help them understand latent needs of SAP's customers and drive huge impact by involving them into the customer co-innovation process.

d) Leading and managing a highly skilled global diverse team of product managers and business development managers.

This is my personal blog and all views expressed are solely mine and not of my current or past employers'. You can also read my other non-technical personal blog: Cutting Chai

If you are reaching out to me for a speaking engagement, please include as much details as you can in your email to expedite my response. I don't take any product briefings and I don't "cover" products or companies.

What's on my Kindle?

Thinking, Fast and Slow: Daniel Kahneman, recipient of the Nobel Prize in Economic Sciences for his seminal work in psychology that challenged the rational model of judgment and decision making, is one of our most important thinkers. His ideas have had a profound and widely regarded impact on many fields—including economics, medicine, and politics—but until now, he has never brought together his many years of research and thinking in one book.

In the highly anticipated Thinking, Fast and Slow, Kahneman takes us on a groundbreaking tour of the mind and explains the two systems that drive the way we think. System 1 is fast, intuitive, and emotional; System 2 is slower, more deliberative, and more logical. Kahneman exposes the extraordinary capabilities—and also the faults and biases—of fast thinking, and reveals the pervasive influence of intuitive impressions on our thoughts and behavior. The impact of loss aversion and overconfidence on corporate strategies, the difficulties of predicting what will make us happy in the future, the challenges of properly framing risks at work and at home, the profound effect of cognitive biases on everything from playing the stock market to planning the next vacation—each of these can be understood only by knowing how the two systems work together to shape our judgments and decisions.

Engaging the reader in a lively conversation about how we think, Kahneman reveals where we can and cannot trust our intuitions and how we can tap into the benefits of slow thinking. He offers practical and enlightening insights into how choices are made in both our business and our personal lives—and how we can use different techniques to guard against the mental glitches that often get us into trouble. Thinking, Fast and Slow will transform the way you think about thinking.

Boomerang: Travels in the New Third World
The tsunami of cheap credit that rolled across the planet between 2002 and 2008 was more than a simple financial phenomenon: it was temptation, offering entire societies the chance to reveal aspects of their characters they could not normally afford to indulge.

Icelanders wanted to stop fishing and become investment bankers. The Greeks wanted to turn their country into a piñata stuffed with cash and allow as many citizens as possible to take a whack at it. The Germans wanted to be even more German; the Irish wanted to stop being Irish.

Michael Lewis's investigation of bubbles beyond our shores is so brilliantly, sadly hilarious that it leads the American reader to a comfortable complacency: oh, those foolish foreigners. But when he turns a merciless eye on California and Washington, DC, we see that the narrative is a trap baited with humor, and we understand the reckoning that awaits the greatest and greediest of debtor nations.

Disclaimer: All the views expressed in this Blog are solely mine and not of my current or past employers'.